Signal processing systems, such as radar and sonar systems, are useful for detecting, characterizing and monitoring various kinematic parameters associated with natural and/or man-made objects, and are important for both civilian and military operations. In radar systems, for example, one or more transmitted electromagnetic (EM) signals, referred to herein as radio frequency (RF) waveforms or pulses, are intended to engage one or more objects or targets. Reflected return signals (or echoes) are received and processed for object identification and characterization. Several types of transmitted signals may be used. For example, single pulse, multiple pulse, and linear frequency modulated (LFM) waveforms may be used, with each waveform type having particular advantages in terms of target detection and velocity and acceleration estimation, by way of example only.
Current signal processing systems have difficulty simultaneously providing high dynamic range, large instantaneous bandwidth, large wideband range window coverage, and high sensitivity in a cost effective manner. More specifically, in the context of radar applications, systems are designed to support either high dynamic range or high sensitivity. Moreover, these systems are limited by their receiver bandwidth. Traditional mitigation approaches are inefficient, requiring multiple pulse repetition intervals (PRIs) to mitigate, including time consumption. For example, multiple PRI frequency waveforms may be employed for large wideband coverage. Moreover, in multiple PRI stretch processing approaches each range window limits a range coverage region according to a ratio of the receiver's intermediate frequency (IF) bandwidth and a desired or target wideband waveform bandwidth.
Improved systems and methods for providing high dynamic range, large instantaneous bandwidth, large wideband range coverage, and high sensitivity in a single system are desired.